4.8 Article

Integrated omics networks reveal the temporal signaling events of brassinosteroid response in Arabidopsis

Journal

NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-26165-3

Keywords

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Funding

  1. USDA-NIFA Postdoctoral Research Fellowship [2019-67012-29712]
  2. National Science Foundation [IOS-2010686]
  3. NSF [MCB-1453130, MCB 1818160]
  4. North Carolina Agricultural & Life Sciences Research Foundation at North Carolina State University's College of Agricultural and Life Sciences
  5. Plant Sciences Institute from Iowa State University

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This study analyzed the BR signaling in Arabidopsis by integrating multiple omics datasets and inferring networks, identifying a BR-regulated transcription factor BRONTOSAURUS that affects cell division in roots. The research provides insights into the molecular signaling events during BR response through integrative network analysis applied to multi-omic data.
Brassinosteroids (BR) regulate plant development and stress responses. Here, by integrating multiple omics datasets and inferring networks, the authors profile BR signaling in Arabidopsis and characterize BRONTOSAURUS, a BR-regulated transcription factor that impacts cell division in roots. Brassinosteroids (BRs) are plant steroid hormones that regulate cell division and stress response. Here we use a systems biology approach to integrate multi-omic datasets and unravel the molecular signaling events of BR response in Arabidopsis. We profile the levels of 26,669 transcripts, 9,533 protein groups, and 26,617 phosphorylation sites from Arabidopsis seedlings treated with brassinolide (BL) for six different lengths of time. We then construct a network inference pipeline called Spatiotemporal Clustering and Inference of Omics Networks (SC-ION) to integrate these data. We use our network predictions to identify putative phosphorylation sites on BES1 and experimentally validate their importance. Additionally, we identify BRONTOSAURUS (BRON) as a transcription factor that regulates cell division, and we show that BRON expression is modulated by BR-responsive kinases and transcription factors. This work demonstrates the power of integrative network analysis applied to multi-omic data and provides fundamental insights into the molecular signaling events occurring during BR response.

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